When using Claude with a very long context (e.g., a 100K token document), where should critical instructions be placed for maximum effectiveness?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Claude (like most LLMs) pays closest attention to the beginning and end of context. Important instructions buried in the middle of 100K tokens are most likely to be missed.
Full explanation below image
Full Explanation
Research on long-context models has identified a 'lost in the middle' phenomenon: models tend to better recall and attend to information at the beginning and end of their context window compared to information in the middle. For a very long context, placing critical instructions at the top (before the document) and/or repeating them at the end improves reliability. Option A (random embedding) is worst practice. Option C proposes instructions after a 100K document — instructions at the very end after massive content may not be as salient as placing them at the beginning. Option D ignores documented positional effects.